chore: import upstream snapshot with attribution

python/samples/02-agents/conversations/suspend_resume_session.py

@@ -0,0 +1,101 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from agent_framework import Agent, AgentSession
+from agent_framework.foundry import FoundryChatClient
+from agent_framework.openai import OpenAIChatCompletionClient
+from azure.identity.aio import AzureCliCredential
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+"""
+Session Suspend and Resume Example
+
+This sample demonstrates how to suspend and resume conversation sessions, comparing
+service-managed sessions (Azure AI) with in-memory sessions (OpenAI) for persistent
+conversation state across sessions.
+"""
+
+
+async def suspend_resume_service_managed_session() -> None:
+    """Demonstrates how to suspend and resume a service-managed session."""
+    print("=== Suspend-Resume Service-Managed Session ===")
+
+    # FoundryChatClient supports service-managed sessions.
+    async with (
+        AzureCliCredential() as credential,
+        Agent(
+            client=FoundryChatClient(credential=credential),
+            name="MemoryBot",
+            instructions="You are a helpful assistant that remembers our conversation.",
+        ) as agent,
+    ):
+        # Start a new session for the agent conversation.
+        session = agent.create_session()
+
+        # Respond to user input.
+        query = "Hello! My name is Alice and I love pizza."
+        print(f"User: {query}")
+        print(f"Agent: {await agent.run(query, session=session)}\n")
+
+        # Serialize the session state, so it can be stored for later use.
+        serialized_session = session.to_dict()
+
+        # The session can now be saved to a database, file, or any other storage mechanism and loaded again later.
+        print(f"Serialized session: {serialized_session}\n")
+
+        # Deserialize the session state after loading from storage.
+        resumed_session = AgentSession.from_dict(serialized_session)
+
+        # Respond to user input.
+        query = "What do you remember about me?"
+        print(f"User: {query}")
+        print(f"Agent: {await agent.run(query, session=resumed_session)}\n")
+
+
+async def suspend_resume_in_memory_session() -> None:
+    """Demonstrates how to suspend and resume an in-memory session."""
+    print("=== Suspend-Resume In-Memory Session ===")
+
+    # OpenAI Chat Client is used as an example here,
+    # other chat clients can be used as well.
+    agent = Agent(
+        client=OpenAIChatCompletionClient(),
+        name="MemoryBot",
+        instructions="You are a helpful assistant that remembers our conversation.",
+    )
+
+    # Start a new session for the agent conversation.
+    session = agent.create_session()
+
+    # Respond to user input.
+    query = "Hello! My name is Alice and I love pizza."
+    print(f"User: {query}")
+    print(f"Agent: {await agent.run(query, session=session)}\n")
+
+    # Serialize the session state, so it can be stored for later use.
+    serialized_session = session.to_dict()
+
+    # The session can now be saved to a database, file, or any other storage mechanism and loaded again later.
+    print(f"Serialized session: {serialized_session}\n")
+
+    # Deserialize the session state after loading from storage.
+    resumed_session = AgentSession.from_dict(serialized_session)
+
+    # Respond to user input.
+    query = "What do you remember about me?"
+    print(f"User: {query}")
+    print(f"Agent: {await agent.run(query, session=resumed_session)}\n")
+
+
+async def main() -> None:
+    print("=== Suspend-Resume Session Examples ===")
+    await suspend_resume_service_managed_session()
+    await suspend_resume_in_memory_session()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())